1. Field of the Invention
The invention relates to a method and apparatus for recognizing characters on a document which is skewed relative to an image scanner.
2. Prior Art
Optical character recognition (OCR) technology has been used to recognize character images on a document. The OCR technology includes the steps of scanning the image of the document, comparing analog signals generated by the scanning operation with a threshold value to generate binary signals representing the image of the document, storing the binary signals in an image buffer, segmenting the character images, that is, breaking the image of the document into separate, distinct images of each character, recognizing the segmented character images, and outputting the results of the recognition.
The prior segmentation includes a step of attempting to separate character rows from each other.
In the case shown in FIGS. 1B and 1C, the character images in the first character row are not separated from the character images in the second character row, whereby two character rows are treated as a single row, so that the characters in the both rows are mixed with each other, and printed out in a single character row of an output print out indicating the results of the OCR of the document. To assure the separation of the character rows, the maximum skew angle for a standard A4 size document is about 1 degree. To perform the separation of the character rows for more skewed documents, the Japanese patent application 56-204636 indicates a solution in which the character rows are separated into plural blocks as shown by vertical dotted lines in the FIG. 3C, and a block projection is generated for each block, and the segmentation of the characters of a block, is made based upon the block projection. Continuity of one block to the next block is recognized to recognize the characters of one character row. Although the patent application 56-204636 somewhat improves the problem, it requires a complicated process for finding out the continuity of the blocks. An inherent problem included in the technology using the projections is that the technology does not successfully operate when the characters and a photograph are mixed in the horizontal direction of the document.
R. L. Hoffman and J. W. McCullough, Segmentation Methods for Recognition of Machine-Printed Characters. IBM Journal of Research and Development, vol. 15 (1971), 153-165, describes an algorithm for separation of touching characters. Scanned characters are examined for their vertical densities (i.e., number of black pixels in each vertical line). and low density lines will be selected as the boundaries of characters. Hence, the method in the article apparently differs from that of the present invention.
K. Y. Wong, R. G. Casey, and F. M. Wahl, Document Analysis System, IBM Journal of Research and Development. vol. 26 (1982), 647-656, describes a general concept of an office system for document analysis. There is a description of a segmentation of characters using the projection method, as described hereinabove. The concept of the article apparently differs from that of the present invention.
R. G. Casey and G. Nagy, Recursive Segmentation and Classification of Composite Character Patterns, Proceedings of 6th International Conference on Pattern Recognition (1982), describes on a segmentation method in the case several characters are connected. As the first step of segmentation, a method presented in the Wong's article is used. The algorithm which is described will be used if the segmented block is supposed to be connected characters. The concept of the article apparently differs from that of the present invention.
R. G. Casey and C. R. Jih, A Processor-Based OCR System, IBM Journal of Research and Development, vol. 27 (1983), 386-399, describes a general method for OCR systems. The algorithm is that characters are segmented after the baseline detection. Also the Decision Tree Algorithm is described here. The article does not disclose the concept of the present invention.
R. G. Casey, S. K. Chai, and K. Y. Wong, Unsupervised Construction of Decision Networks for Pattern Classification, Proceedings of IEEE 7th International Conference on Pattern Recognition (1984), describes a recognition algorithm, and there is no description on the segmentation.